Three Thousand Seven Hundred Thirty-Eight Posttraumatic Pulmonary Emboli
Bibliographic record
Abstract
OBJECTIVE: This study was undertaken to determine the current incidence of pulmonary embolism (PE) and its attributable mortality after injury. BACKGROUND: Despite compliance with prophylactic measures, PE remains a threat to postinjury recovery. We hypothesized that the liberal use of chest computed tomography after injury has resulted in an increased rate of detection of PE but that the mortality attributable to PE has decreased over the past decade. We also postulated that the risk factors for posttraumatic PE might be different from those for deep venous thrombosis (DVT). METHODS: We examined demographics, injury data, risk factors, and outcomes from patients with DVT and PE compiled in the recent years (2007-2009) in the National Trauma Data Bank (NTDB). For comparison, we used patient data entered into NTDB from 1994 to 2001. Statistical models were created to examine the predictors of DVT and PE and PE-related mortality. RESULTS: Among 888,652 patients in the current NTDB cohort, there were 9398 episodes of DVT (1.06%) and 3738 of PE (0.42%). Although many risk factors overlapped, a severe chest injury (Abbreviated Injury Score ≥ 3) conferred a much higher risk of PE than DVT. When comparing results from centers that had contributed to both data sets, there was a more than 2-fold increase in PE occurrence in the current cohort (0.49% vs 0.21%, P < 0.01) but with a significant reduction in PE-adjusted mortality (odds ratio, 4.08 vs 2.42). CONCLUSIONS: The reported incidence of PE after trauma has more than doubled in recent years, while the PE-associated mortality has significantly decreased, suggesting that we are identifying a different disease entity or stage. Chest injuries convey a substantial risk for PE, a risk not likely to be diminished by leg compression devices or vena cava filters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".